// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2010 Benoit Jacob <jacob.benoit.1@gmail.com>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

#include "main.h"

template<int Alignment, typename VectorType>
void
map_class_vector(const VectorType& m)
{
	typedef typename VectorType::Scalar Scalar;

	Index size = m.size();

	VectorType v = VectorType::Random(size);

	Index arraysize = 3 * size;

	Scalar* a_array = internal::aligned_new<Scalar>(arraysize + 1);
	Scalar* array = a_array;
	if (Alignment != Aligned)
		array = (Scalar*)(internal::IntPtr(a_array) + (internal::packet_traits<Scalar>::AlignedOnScalar
														   ? sizeof(Scalar)
														   : sizeof(typename NumTraits<Scalar>::Real)));

	{
		Map<VectorType, Alignment, InnerStride<3>> map(array, size);
		map = v;
		for (int i = 0; i < size; ++i) {
			VERIFY(array[3 * i] == v[i]);
			VERIFY(map[i] == v[i]);
		}
	}

	{
		Map<VectorType, Unaligned, InnerStride<Dynamic>> map(array, size, InnerStride<Dynamic>(2));
		map = v;
		for (int i = 0; i < size; ++i) {
			VERIFY(array[2 * i] == v[i]);
			VERIFY(map[i] == v[i]);
		}
	}

	internal::aligned_delete(a_array, arraysize + 1);
}

template<int Alignment, typename MatrixType>
void
map_class_matrix(const MatrixType& _m)
{
	typedef typename MatrixType::Scalar Scalar;

	Index rows = _m.rows(), cols = _m.cols();

	MatrixType m = MatrixType::Random(rows, cols);
	Scalar s1 = internal::random<Scalar>();

	Index arraysize = 4 * (rows + 4) * (cols + 4);

	Scalar* a_array1 = internal::aligned_new<Scalar>(arraysize + 1);
	Scalar* array1 = a_array1;
	if (Alignment != Aligned)
		array1 = (Scalar*)(internal::IntPtr(a_array1) + (internal::packet_traits<Scalar>::AlignedOnScalar
															 ? sizeof(Scalar)
															 : sizeof(typename NumTraits<Scalar>::Real)));

	Scalar a_array2[256];
	Scalar* array2 = a_array2;
	if (Alignment != Aligned)
		array2 = (Scalar*)(internal::IntPtr(a_array2) + (internal::packet_traits<Scalar>::AlignedOnScalar
															 ? sizeof(Scalar)
															 : sizeof(typename NumTraits<Scalar>::Real)));
	else
		array2 = (Scalar*)(((internal::UIntPtr(a_array2) + EIGEN_MAX_ALIGN_BYTES - 1) / EIGEN_MAX_ALIGN_BYTES) *
						   EIGEN_MAX_ALIGN_BYTES);
	Index maxsize2 = a_array2 - array2 + 256;

	// test no inner stride and some dynamic outer stride
	for (int k = 0; k < 2; ++k) {
		if (k == 1 && (m.innerSize() + 1) * m.outerSize() > maxsize2)
			break;
		Scalar* array = (k == 0 ? array1 : array2);

		Map<MatrixType, Alignment, OuterStride<Dynamic>> map(
			array, rows, cols, OuterStride<Dynamic>(m.innerSize() + 1));
		map = m;
		VERIFY(map.outerStride() == map.innerSize() + 1);
		for (int i = 0; i < m.outerSize(); ++i)
			for (int j = 0; j < m.innerSize(); ++j) {
				VERIFY(array[map.outerStride() * i + j] == m.coeffByOuterInner(i, j));
				VERIFY(map.coeffByOuterInner(i, j) == m.coeffByOuterInner(i, j));
			}
		VERIFY_IS_APPROX(s1 * map, s1 * m);
		map *= s1;
		VERIFY_IS_APPROX(map, s1 * m);
	}

	// test no inner stride and an outer stride of +4. This is quite important as for fixed-size matrices,
	// this allows to hit the special case where it's vectorizable.
	for (int k = 0; k < 2; ++k) {
		if (k == 1 && (m.innerSize() + 4) * m.outerSize() > maxsize2)
			break;
		Scalar* array = (k == 0 ? array1 : array2);

		enum
		{
			InnerSize = MatrixType::InnerSizeAtCompileTime,
			OuterStrideAtCompileTime = InnerSize == Dynamic ? Dynamic : InnerSize + 4
		};
		Map<MatrixType, Alignment, OuterStride<OuterStrideAtCompileTime>> map(
			array, rows, cols, OuterStride<OuterStrideAtCompileTime>(m.innerSize() + 4));
		map = m;
		VERIFY(map.outerStride() == map.innerSize() + 4);
		for (int i = 0; i < m.outerSize(); ++i)
			for (int j = 0; j < m.innerSize(); ++j) {
				VERIFY(array[map.outerStride() * i + j] == m.coeffByOuterInner(i, j));
				VERIFY(map.coeffByOuterInner(i, j) == m.coeffByOuterInner(i, j));
			}
		VERIFY_IS_APPROX(s1 * map, s1 * m);
		map *= s1;
		VERIFY_IS_APPROX(map, s1 * m);
	}

	// test both inner stride and outer stride
	for (int k = 0; k < 2; ++k) {
		if (k == 1 && (2 * m.innerSize() + 1) * (m.outerSize() * 2) > maxsize2)
			break;
		Scalar* array = (k == 0 ? array1 : array2);

		Map<MatrixType, Alignment, Stride<Dynamic, Dynamic>> map(
			array, rows, cols, Stride<Dynamic, Dynamic>(2 * m.innerSize() + 1, 2));
		map = m;
		VERIFY(map.outerStride() == 2 * map.innerSize() + 1);
		VERIFY(map.innerStride() == 2);
		for (int i = 0; i < m.outerSize(); ++i)
			for (int j = 0; j < m.innerSize(); ++j) {
				VERIFY(array[map.outerStride() * i + map.innerStride() * j] == m.coeffByOuterInner(i, j));
				VERIFY(map.coeffByOuterInner(i, j) == m.coeffByOuterInner(i, j));
			}
		VERIFY_IS_APPROX(s1 * map, s1 * m);
		map *= s1;
		VERIFY_IS_APPROX(map, s1 * m);
	}

	// test inner stride and no outer stride
	for (int k = 0; k < 2; ++k) {
		if (k == 1 && (m.innerSize() * 2) * m.outerSize() > maxsize2)
			break;
		Scalar* array = (k == 0 ? array1 : array2);

		Map<MatrixType, Alignment, InnerStride<Dynamic>> map(array, rows, cols, InnerStride<Dynamic>(2));
		map = m;
		VERIFY(map.outerStride() == map.innerSize() * 2);
		for (int i = 0; i < m.outerSize(); ++i)
			for (int j = 0; j < m.innerSize(); ++j) {
				VERIFY(array[map.innerSize() * i * 2 + j * 2] == m.coeffByOuterInner(i, j));
				VERIFY(map.coeffByOuterInner(i, j) == m.coeffByOuterInner(i, j));
			}
		VERIFY_IS_APPROX(s1 * map, s1 * m);
		map *= s1;
		VERIFY_IS_APPROX(map, s1 * m);
	}

	// test negative strides
	{
		Matrix<Scalar, Dynamic, 1>::Map(a_array1, arraysize + 1).setRandom();
		Index outerstride = m.innerSize() + 4;
		Scalar* array = array1;

		{
			Map<MatrixType, Alignment, OuterStride<>> map1(array, rows, cols, OuterStride<>(outerstride));
			Map<MatrixType, Unaligned, OuterStride<>> map2(
				array + (m.outerSize() - 1) * outerstride, rows, cols, OuterStride<>(-outerstride));
			if (MatrixType::IsRowMajor)
				VERIFY_IS_APPROX(map1.colwise().reverse(), map2);
			else
				VERIFY_IS_APPROX(map1.rowwise().reverse(), map2);
		}

		{
			Map<MatrixType, Alignment, OuterStride<>> map1(array, rows, cols, OuterStride<>(outerstride));
			Map<MatrixType, Unaligned, Stride<Dynamic, Dynamic>> map2(array + (m.outerSize() - 1) * outerstride +
																		  m.innerSize() - 1,
																	  rows,
																	  cols,
																	  Stride<Dynamic, Dynamic>(-outerstride, -1));
			VERIFY_IS_APPROX(map1.reverse(), map2);
		}

		{
			Map<MatrixType, Alignment, OuterStride<>> map1(array, rows, cols, OuterStride<>(outerstride));
			Map<MatrixType, Unaligned, Stride<Dynamic, -1>> map2(array + (m.outerSize() - 1) * outerstride +
																	 m.innerSize() - 1,
																 rows,
																 cols,
																 Stride<Dynamic, -1>(-outerstride, -1));
			VERIFY_IS_APPROX(map1.reverse(), map2);
		}
	}

	internal::aligned_delete(a_array1, arraysize + 1);
}

// Additional tests for inner-stride but no outer-stride
template<int>
void
bug1453()
{
	const int data[] = { 0,	 1,	 2,	 3,	 4,	 5,	 6,	 7,	 8,	 9,	 10, 11, 12, 13, 14, 15,
						 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 };
	typedef Matrix<int, Dynamic, Dynamic, RowMajor> RowMatrixXi;
	typedef Matrix<int, 2, 3, ColMajor> ColMatrix23i;
	typedef Matrix<int, 3, 2, ColMajor> ColMatrix32i;
	typedef Matrix<int, 2, 3, RowMajor> RowMatrix23i;
	typedef Matrix<int, 3, 2, RowMajor> RowMatrix32i;

	VERIFY_IS_APPROX(MatrixXi::Map(data, 2, 3, InnerStride<2>()), MatrixXi::Map(data, 2, 3, Stride<4, 2>()));
	VERIFY_IS_APPROX(MatrixXi::Map(data, 2, 3, InnerStride<>(2)), MatrixXi::Map(data, 2, 3, Stride<4, 2>()));
	VERIFY_IS_APPROX(MatrixXi::Map(data, 3, 2, InnerStride<2>()), MatrixXi::Map(data, 3, 2, Stride<6, 2>()));
	VERIFY_IS_APPROX(MatrixXi::Map(data, 3, 2, InnerStride<>(2)), MatrixXi::Map(data, 3, 2, Stride<6, 2>()));

	VERIFY_IS_APPROX(RowMatrixXi::Map(data, 2, 3, InnerStride<2>()), RowMatrixXi::Map(data, 2, 3, Stride<6, 2>()));
	VERIFY_IS_APPROX(RowMatrixXi::Map(data, 2, 3, InnerStride<>(2)), RowMatrixXi::Map(data, 2, 3, Stride<6, 2>()));
	VERIFY_IS_APPROX(RowMatrixXi::Map(data, 3, 2, InnerStride<2>()), RowMatrixXi::Map(data, 3, 2, Stride<4, 2>()));
	VERIFY_IS_APPROX(RowMatrixXi::Map(data, 3, 2, InnerStride<>(2)), RowMatrixXi::Map(data, 3, 2, Stride<4, 2>()));

	VERIFY_IS_APPROX(ColMatrix23i::Map(data, InnerStride<2>()), MatrixXi::Map(data, 2, 3, Stride<4, 2>()));
	VERIFY_IS_APPROX(ColMatrix23i::Map(data, InnerStride<>(2)), MatrixXi::Map(data, 2, 3, Stride<4, 2>()));
	VERIFY_IS_APPROX(ColMatrix32i::Map(data, InnerStride<2>()), MatrixXi::Map(data, 3, 2, Stride<6, 2>()));
	VERIFY_IS_APPROX(ColMatrix32i::Map(data, InnerStride<>(2)), MatrixXi::Map(data, 3, 2, Stride<6, 2>()));

	VERIFY_IS_APPROX(RowMatrix23i::Map(data, InnerStride<2>()), RowMatrixXi::Map(data, 2, 3, Stride<6, 2>()));
	VERIFY_IS_APPROX(RowMatrix23i::Map(data, InnerStride<>(2)), RowMatrixXi::Map(data, 2, 3, Stride<6, 2>()));
	VERIFY_IS_APPROX(RowMatrix32i::Map(data, InnerStride<2>()), RowMatrixXi::Map(data, 3, 2, Stride<4, 2>()));
	VERIFY_IS_APPROX(RowMatrix32i::Map(data, InnerStride<>(2)), RowMatrixXi::Map(data, 3, 2, Stride<4, 2>()));
}

EIGEN_DECLARE_TEST(mapstride)
{
	for (int i = 0; i < g_repeat; i++) {
		int maxn = 3;
		CALL_SUBTEST_1(map_class_vector<Aligned>(Matrix<float, 1, 1>()));
		CALL_SUBTEST_1(map_class_vector<Unaligned>(Matrix<float, 1, 1>()));
		CALL_SUBTEST_2(map_class_vector<Aligned>(Vector4d()));
		CALL_SUBTEST_2(map_class_vector<Unaligned>(Vector4d()));
		CALL_SUBTEST_3(map_class_vector<Aligned>(RowVector4f()));
		CALL_SUBTEST_3(map_class_vector<Unaligned>(RowVector4f()));
		CALL_SUBTEST_4(map_class_vector<Aligned>(VectorXcf(internal::random<int>(1, maxn))));
		CALL_SUBTEST_4(map_class_vector<Unaligned>(VectorXcf(internal::random<int>(1, maxn))));
		CALL_SUBTEST_5(map_class_vector<Aligned>(VectorXi(internal::random<int>(1, maxn))));
		CALL_SUBTEST_5(map_class_vector<Unaligned>(VectorXi(internal::random<int>(1, maxn))));

		CALL_SUBTEST_1(map_class_matrix<Aligned>(Matrix<float, 1, 1>()));
		CALL_SUBTEST_1(map_class_matrix<Unaligned>(Matrix<float, 1, 1>()));
		CALL_SUBTEST_2(map_class_matrix<Aligned>(Matrix4d()));
		CALL_SUBTEST_2(map_class_matrix<Unaligned>(Matrix4d()));
		CALL_SUBTEST_3(map_class_matrix<Aligned>(Matrix<float, 3, 5>()));
		CALL_SUBTEST_3(map_class_matrix<Unaligned>(Matrix<float, 3, 5>()));
		CALL_SUBTEST_3(map_class_matrix<Aligned>(Matrix<float, 4, 8>()));
		CALL_SUBTEST_3(map_class_matrix<Unaligned>(Matrix<float, 4, 8>()));
		CALL_SUBTEST_4(
			map_class_matrix<Aligned>(MatrixXcf(internal::random<int>(1, maxn), internal::random<int>(1, maxn))));
		CALL_SUBTEST_4(
			map_class_matrix<Unaligned>(MatrixXcf(internal::random<int>(1, maxn), internal::random<int>(1, maxn))));
		CALL_SUBTEST_5(
			map_class_matrix<Aligned>(MatrixXi(internal::random<int>(1, maxn), internal::random<int>(1, maxn))));
		CALL_SUBTEST_5(
			map_class_matrix<Unaligned>(MatrixXi(internal::random<int>(1, maxn), internal::random<int>(1, maxn))));
		CALL_SUBTEST_6(
			map_class_matrix<Aligned>(MatrixXcd(internal::random<int>(1, maxn), internal::random<int>(1, maxn))));
		CALL_SUBTEST_6(
			map_class_matrix<Unaligned>(MatrixXcd(internal::random<int>(1, maxn), internal::random<int>(1, maxn))));

		CALL_SUBTEST_5(bug1453<0>());

		TEST_SET_BUT_UNUSED_VARIABLE(maxn);
	}
}
